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Medical Statistics from Scratch

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This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to el... Weiterlesen
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Beschreibung

This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to elementary statistics. The book presents a detailed account of the most important procedures for the analysis of data, from the calculation of simple proportions, to a variety of statistical tests, and the use of regression models for modeling of clinical outcomes.

The level of mathematics is kept to a minimum to make the material easily accessible to the novice, and a multitude of illustrative cases are included in every chapter, drawn from the current research literature. The new edition has been completely revised and updated and includes new chapters on basic quantitative methods, measuring survival, measurement scales, diagnostic testing, bayesian methods, meta-analysis and systematic reviews.

'... After years of trying and failing, this is the only book on statistics that i have managed to read and understand' - Naveed Kirmani, Surgical Registrar, South London Healthcare HHS Trust, UK

 



David Bowers, School of Medicine, University of Leeds, UK.

Autorentext
David Bowers, School of Medicine, University of Leeds, UK.

Klappentext
The second edition of this highly successful, user-friendly book, continues to provide an excellent foundation in statistics for the uninitiated, making it ideal for both students and professionals in health care and medicine who may be either approaching the subject for the first time, or who want to refresh their understanding of any one of a number of statistical concepts and applications.

As with the first edition, the informal and light-hearted style, and the author's avoidance of too much mathematics, makes the material very accessible. The addition of two new chapters, one on survival analysis, the other on systematic review and meta-analysis, significantly improves the coverage offered.

New in this edition:

  • Measuring survival: Kaplan-Meier survival curves; comparing survival in two or more groups.Hazard ratios and the Cox regression model.
  • Systematic review: methods and problems; combining results - meta-analytic methods.

Reviews of first edition:

"His (the author's) work can be highly recommended for health workers, medical students and any other professionals who are revising statistics or approaching it for the first time."
Statistical Methods in Medical Research

"This basic book is exciting and fun to read. Information is presented in a digestable and humorous format. Examples are appropriate to each subject area and easily understood."
Clinical Trials

  • Contains work-through examples, using up-to-date, illustrative data.
  • Gives insightful examples of the use of the SPSS and Minitab statistics
  • programmes for some common applications.
  • Provides lots of exercises to improve understanding and consolidate learning


Inhalt
Preface to the 1st Edition.

Preface to the 2nd Edition.

Introduction.

I Some fundamental stuff.

1 First things first the nature of data.

Learning objectives.

Variables and data.

The good, the bad and the ugly - types of variable.

Categorical variables.

Metric variables.

II Descriptive statistics.

2 Describing data with tables.

Learning objectives.

What is descriptive statistics?

The frequency table.

3 Describing data with charts.

Learning objectives Picture it!

Charting nominal and ordinal data Charting discrete metric data.

Charting continuous metric data.

Charting cumulative data.

4 Describing data from its distributional shape Learning objectives.

The shape of things to come.

5 Describing data with numeric summary values.

Learning objectives.

Numbers R us.

Summary measures of location.

Summary measures of spread.

Standard deviation and the Normal distribution.

III Getting the data.

6 Doing it right first time designing a study Learning objectives.

Hey ho! Hey ho! It's off to work we go.

Collecting the data - types of sample Types of study.

Confounding.

Matching.

Comparing cohort and case-control designs.

Getting stuck in - experimental studies.

IV From little to large statistical inference.

7 From samples to populations making inferences.

Learning objectives.

Statistical inference.

8 Probability, risk and odds

Learning objectives.

Chance would be a fine thing - the idea of probability.

Calculating probability.

Probability and the Normal distribution.

Risk.

Odds.

Why you can't calculate risk in a case-control study.

The link between probability and odds.

The risk ratio.

The odds ratio.

Number needed to treat .

V The informed guess - confidence interval estimation.

9 Estimating the value of a single population parameter - the idea of confidence intervals.

Learning objectives.

Confidence interval estimation for a population mean.

Confidence interval for a population proportion.

Estimating a confidence interval for the median of a single population.

10 Estimating the differences between two population parameters.

Learning objectives.

What's the difference?

Estimating the difference between the means of two independent populations using a method based on the two-sample t test.

Estimating the difference between two matched population means using a method based on the matched-pairs t test.

Estimating the difference between two independent population proportions.

Estimating the difference between two independent population medians the MannWhitney rank-sums method.

Estimating the difference between two matched population medians - Wilcoxon signed-ranks method.

11 Estimating the ratio of two population parameters.

Learning objectives.

Estimating ratios of means, risks and odds.

VI Putting it to the test.

12 Testing hypotheses about the difference between two population parameters.

Learning objectives.

The research question and the hypothesis test.

A brief summary of a few of the commonest tests.

Some examples of hypothesis tests from practice.

Confidence intervals versus hypothesis testing.

Nobody's perfect - types of error.

The power of a test.

Maximising power - calculating sample size.

Rules of thumb.

13 Testing hypotheses about the ratio of two population parameters.

Learning objectives.

Testing the risk ratio.

Testing the odds ratio.

14 Testing hypotheses about the equality of two or more proportions.

Learning objectives.

Of all the tests in all the world...the chi-squared (?2) test.

VII Getting up close.

15 Measuring the association between two variables.

Learning objectives.

Association.

The correlation coefficient.

16 Measuring the agreement between two variables.

Learning objectives.

To agree or not agree: that is the question.

Cohen's kappa.

Measuring agreement with ordinal data - weighted kappa.

Measuring the agreement between two metric continuous variables.

VIII Getting into a relationship.

17 Straight-line models - linear regression.

Learning objectives.

Health warning!

Relationship and association.

The linear regression model.<...

Produktinformationen

Titel: Medical Statistics from Scratch
Untertitel: An Introduction for Health Professionals
Autor:
EAN: 9780470724446
ISBN: 978-0-470-72444-6
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (pdf)
Herausgeber: Wiley-Interscience
Genre: Allgemeines
Anzahl Seiten: 300
Veröffentlichung: 15.04.2008
Jahr: 2008
Auflage: 2. Aufl.
Untertitel: Englisch
Dateigrösse: 7.3 MB